Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments
Figure 3
SAS code for classical ANOVA and EGLS
inference. Comments describing purpose
immediately provided after corresponding code between /* and */ as with a regular
SAS program. EGLS based on REML would
simply involve substituting method = reml for method
= type3 in the third line of the code.
title “Mixed model analysis of log fluorescence
intensity data from gene 30”;
proc mixed
data=gene30 /* name of data
as provided in Table 4*/
method = type3;
/* Provides
classical ANOVA table and EGLS based on ANOVA estimates of VC */
/* If REML
estimates of VC are desired, change above line to method = reml; */
where ((array <= 9) or (15 <=array
<= 23));
/* Using A-loop
component (arrays 1-9, 15-23) of Table 4 data only */
class rep array inoc
time dye;
/* name of fixed
and random classification factors in design */
model ly = inoc time
inoc*time dye
/* Specify
response variable and fixed effects here */
/ddfm = kr
/* Use
Kenward-Roger's procedure to estimate denominator degrees of freedom */
e3;
/* e3 will print
the contrast matrices KA, KB and KAB (see (A.8), (A.9) and
(A.10) of Appendix 5) used to provide the
EGLS ANOVA F-test statistics (optional) */
random array(time) rep(inoc*time)
; /*
Specify random effects */
estimate “k1 contrast”
int 0 inoc 1 1 0 time 0 00 inoc*time 1 00 1 00 00 0 dye 0 0;
/* contrast
coefficients as specified for k1 in (A.6) of Appendix 5*/
estimate “k2 contrast”
int 0 inoc 0 00 time 1 1 0 inoc*time 1 1 00 00 00 0 dye 0 0;
/* contrast
coefficients as specified for k2 in (A.7) of Appendix 5*/
